Double embedding-transfer-based multi-view spectral clustering

作者：

Highlights：

• A multi-view clustering model is proposed to mine the consistency of multi-view data.

• This jointly learns consistency and feature embedding in a unified framework.

• Bipartite graph co-clustering achieves knowledge transfer between the two embeddings.

摘要

•A multi-view clustering model is proposed to mine the consistency of multi-view data.•This jointly learns consistency and feature embedding in a unified framework.•Bipartite graph co-clustering achieves knowledge transfer between the two embeddings.

论文关键词：Embedding transfer,Multi-view,Spectral clustering,Co-regularization

论文评审过程：Received 27 November 2021, Revised 12 July 2022, Accepted 1 August 2022, Available online 6 August 2022, Version of Record 13 August 2022.

论文官网地址：https://doi.org/10.1016/j.eswa.2022.118374